*Joint work with Prof.Vishal
Product reviews are considered as one of the most trusted sources by consumers
| Review | Reviewer | Product |
|---|---|---|
| Star Rating | Reviewer Name | Product Name |
| Length | Gender | Average Rating |
| Text | Geography | Price |
| Time | Total Reviews (heavy/light) | Broad Category |
| Helpfulness | Popularity/Sales |
Text features: standard NLP
Readability
Sentiment
Highly correlated in the data
Someone is Watching: Impact of Amazon’s Policy Change on Reviews
Today: What makes a review helpful?
Star Rating
Imagine the average rating for a product is 4.5, which review do you think is more helpful? 1 star, 3 star or 5 star?
“There is a general bias, based on both innate predispositions and experience, in animals and humans, to give greater weight to negative entities (e.g., events, objects, personal traits)” Rozin & Royzman (2011)
Product has at least 5 reviews; review has at least 5 votes; before 2014
Relative star: absolute above 0.5
All other numeric variables are scaled to mean 0
Processing on HPC clusters at Stern
helpfulness=ReviewLevel+ReviewerLevel+ProductLevel
Thank you
(let’s dance)
Mixed findings
Publishing while Female: Gender Differences in Peer Review Scrutiny Erin Hengel 2017
Anindya Ghose, Panagiotis G. Ipeirotis. 2010. “Estimating the Helpfulness and Economic Impact of Product Reviews.” Ieee Transactions on Knowledge and Data Engineering, 1–15. doi:10.1109/TKDE.2010.188.
Baek, Hyunmi, JoongHo Ahn, and Youngseok Choi. 2012. “Helpfulness of Online Consumer Reviews: Readers’ Objectives and Review Cues.” International Journal of Electronic Commerce 17 (2). Taylor & Francis: 99–126.
Chen, Pei-Yu, Samita Dhanasobhon, and Michael D Smith. 2008. “All Reviews Are Not Created Equal: The Disaggregate Impact of Reviews and Reviewers at Amazon. Com.” Com (May 2008).
Filieri, Raffaele. 2015. “What Makes Online Reviews Helpful? A Diagnosticity-Adoption Framework to Explain Informational and Normative Influences in E-Wom.” Journal of Business Research 68 (6). Elsevier: 1261–70.
Hu, Nan, Indranil Bose, Noi Sian, and Ling Liu. 2012. “Manipulation of online reviews : An analysis of ratings , readability , and sentiments.” Decision Support Systems 52 (3). Elsevier B.V.: 674–84. doi:10.1016/j.dss.2011.11.002.
Korfiatis, Nikolaos, Elena García-Bariocanal, and Salvador Sánchez-Alonso. 2012. “Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content.” Electronic Commerce Research and Applications 11 (3). Elsevier B.V.: 205–17. doi:10.1016/j.elerap.2011.10.003.
Mudambi, Susan M, and David Schuff. 2010. “What Makes a Helpful Review? A Study of Customer Reviews on Amazon. Com.” MIS Quarterly 34 (1): 185–200.
Pan, Yue, and Jason Q Zhang. 2011. “Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews.” Journal of Retailing 87 (4). Elsevier: 598–612.
Racherla, Pradeep, and Wesley Friske. 2012. “Perceived ‘Usefulness’ of Online Consumer Reviews: An Exploratory Investigation Across Three Services Categories.” Electronic Commerce Research and Applications 11 (6). Elsevier: 548–59.